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Pathways to HIV risk and vulnerability among lesbian, gay, bisexual, and transgendered methamphetamine… Marshall, Brandon D; Wood, Evan; Shoveller, Jean A; Patterson, Thomas L; Montaner, Julio S; Kerr, Thomas Jan 7, 2011

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RESEARCH ARTICLE Open AccessPathways to HIV risk and vulnerability amonglesbian, gay, bisexual, and transgenderedmethamphetamine users: a multi-cohortgender-based analysisBrandon DL Marshall1,2, Evan Wood1,3, Jean A Shoveller2, Thomas L Patterson4, Julio SG Montaner1,3,Thomas Kerr1,3*AbstractBackground: Methamphetamine (MA) use continues to be a major public health concern in many urban settings.We sought to assess potential relationships between MA use and individual, social, and structural HIV vulnerabilitiesamong sexual minority (lesbian, gay, bisexual or transgendered) drug users.Methods: Beginning in 2005 and ending in 2008, 2109 drug users were enroled into one of three cohort studiesin Vancouver, Canada. We analysed longitudinal data from all self-identified sexual minority participants (n = 248).Logistic regression using generalized estimating equations (GEE) was used to examine the independent correlatesof MA use over time. All analyses were stratified by biological sex at birth.Results: At baseline, 104 (7.5%) males and 144 (20.4%) females reported sexual minority status, among whom 64(62.1%) and 58 (40.3%) reported MA use in the past six months, respectively. Compared to heterosexualparticipants, sexual minority males (odds ratio [OR] = 3.74, p < 0.001) and females (OR = 1.80, p = 0.003) weremore likely to report recent MA use. In multivariate analysis, MA use among sexual minority males was associatedwith younger age (adjusted odds ratio [AOR] = 0.93 per year older, p = 0.011), Aboriginal ancestry (AOR = 2.59, p= 0.019), injection drug use (AOR = 3.98, p < 0.001), having a legal order or area restriction (i.e., “no-go zone”)impact access to services or influence where drugs are used or purchased (AOR = 4.18, p = 0.008), unprotectedintercourse (AOR = 1.62, p = 0.048), and increased depressive symptoms (AOR = 1.67, p = 0.044). Among females,MA use was associated with injection drug use (AOR = 2.49, p = 0.002), Downtown South residency (i.e., an areaknown for drug use) (AOR = 1.60, p = 0.047), and unprotected intercourse with sex trade clients (AOR = 2.62,p = 0.027).Conclusions: Methamphetamine use was more prevalent among sexual minority males and females and wasassociated with different sets of HIV risks and vulnerabilities. Our findings suggest that interventions addressingMA-related harms may need to be informed by more nuanced understandings of the intersection between druguse patterns, social and structural HIV vulnerabilities, and gender/sexual identities. In particular, MA-focusedprevention and treatment programs tailored to disenfranchised male and female sexual minority youth arerecommended.* Correspondence: uhritk@cfenet.ubc.ca1British Columbia Centre for Excellence in HIV/AIDS, St. Paul’s Hospital, 608-1081 Burrard Street, Vancouver, BC, V6Z 1Y6, CanadaFull list of author information is available at the end of the articleMarshall et al. BMC Public Health 2011, 11:20http://www.biomedcentral.com/1471-2458/11/20© 2011 Marshall et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative CommonsAttribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction inany medium, provided the original work is properly cited.BackgroundLike many other marginalised groups, lesbian, gay,bisexual, and transgendered (LGBT) populations experi-ence a range of health inequities and vulnerabilitiescompared to the general population [1]. In addition tothe multiple health conditions that disproportionatelyaffect LGBT populations, sexual minorities also experi-ence significant barriers to accessing appropriate careand prevention services [2,3]. Due in part to the histori-cal invisibility of LGBT persons and a reluctance amongsome communities to consider sexual minorities as a“legitimate” marginalised group, this population con-tinues to be underrepresented in public health researchand practice [4].A number of studies have demonstrated a high preva-lence of substance use and dependence among sexualminority groups [5,6]. For example, methamphetamine(MA) use has been well studied among gay, bisexual,and other men who have sex with men (MSM), particu-larly in relation to increased sexual risk behaviour andHIV transmission [7-9]. Although much less researchhas been conducted among sexual minority women, sev-eral cross sectional studies have demonstrated that les-bian and bisexual-identified females report significantlyhigher rates of MA use [10,11]. MA use among womenwho inject drugs (IDU) has also been associated withsexual- and injection-related HIV risk behaviour [12].These studies and other research imply important gen-der differences in the typologies of and adverse healthoutcomes associated with MA use [13]; therefore, gen-der-based analyses involving sexual minority populationsare needed to better inform effective public healthapproaches and practice.Although the individual and psychosocial factors thatdrive HIV risk within the context of MA use are rela-tively well understood [14-16], research has only begunto elucidate how environmental and structural determi-nants link MA use with increased HIV vulnerability[17]. In order to most effectively reduce MA-relatedexposure to HIV risks, several authors have called forthe investigation of personal, social, environmental, andstructural correlates of MA use and harms [17,18]. The“risk environment” framework, which posits that factorsexogenous to the individual intersect to (re)-produceHIV risk and other drug-related harms [19], providesone such conceptual model to guide investigation of theassociations between MA use and HIV vulnerabilitiesoperating at various levels of influence.Using data collected from three large ongoing pro-spective cohort studies of drug users in Vancouver,Canada, we sought to determine the prevalence of MAuse among sexual minority males and females. Further-more, relying on a risk environment approach, weassessed the relationships between MA use and a rangeof individual, social, and structural HIV-related vulner-abilities with the aim of indentifying through whichpathways MA use may exacerbate exposure to HIV risk.MethodsStudy DesignThe At Risk Youth Study (ARYS), Vancouver InjectionDrug Users Study (VIDUS) and AIDS Care Cohort toEvaluate Access to Survival Services (ACCESS) are openprospective cohorts of drug users in Vancouver, Canada.These studies comprise a larger program of researchfocused on the study of the initiation and natural historyof injection drug use, and are administered by oneresearch centre (i.e., the British Columbia Centre forExcellence in HIV/AIDS). The risk environment frame-work is utilized as the theoretical foundation fromwhich to examine how a variety of factors within social,physical, and political space interact to (re)-produceHIV and drug-related harm [19]. Recruitment proce-dures for the three studies are similar, with the primarymodes of enrolment being self-referral, word of mouth,and street outreach. Participants of all studies must haveresided in the greater Vancouver region and providedinformed consent to be eligible. Each study also hadspecific eligibility criteria that are detailed briefly here.ARYS consists of drug-using street-involved youth; thus,eligibility criteria included being between the age of 14and 26 and the use of illicit drugs other than or in addi-tion to marijuana in the past 30 days. VIDUS is a studyof HIV-negative IDU in which all participants musthave injected an illicit drug in the past 6 months to beeligible for inclusion. ACCESS is a cohort of HIV-posi-tive individuals, who, similar to those in ARYS, musthave recently used an illicit drug other than or in addi-tion to marijuana. Detailed sampling and recruitmentprocedures for these three cohorts have been describedelsewhere [20-22]. In this analysis, we combined datafrom all three studies to achieve a sample size with suf-ficient power to examine MA use among the sub-sampleof participants who identified as a sexual minority.While combining data from studies with different inclu-sion criteria may present some challenges, we note thatall studies rely on harmonized recruitment and data col-lection tools. Furthermore, combining the datasets per-mitted an examination of MA use patterns across adiverse spectrum of drug users (e.g., street-involvedyouth, older IDU) in our setting.At baseline and semi-annually, participants completeda lengthy interviewer-administered questionnaire. Socio-demographic data, as well as information pertaining todrug use patterns, risk behaviours, and health care utili-sation are collected. The survey for each study consistsMarshall et al. BMC Public Health 2011, 11:20http://www.biomedcentral.com/1471-2458/11/20Page 2 of 10of a uniform set of questions, which permits the aggre-gation and analysis of data from all enrolled participants.Nurses collected blood specimens for HIV and hepatitisC serology and also provided basic medical care andreferrals to appropriate health care services. Participantsreceived $20 for each study visit. All studies have beenapproved by the University of British Columbia/Provi-dence Health Care Research Ethics Board.Study SampleData from each cohort used in this analysis was col-lected during the same time frame; thus, all individualswere observed over the same follow-up period. All parti-cipants who completed a baseline survey between Sep-tember 2005 and May 2008 were eligible for inclusion.At baseline, participants were asked to identify their bio-logical sex at birth and their current sexual orientation.“Sexual minority status” was defined as answering affir-matively to one of: gay, lesbian, bisexual, transsexual,transgendered, or other. Participants who refused toreport their sex at birth or current sexual and genderidentity were excluded from this analysis.Study HypothesesThe primary hypothesis guiding this analysis was basedon the risk environment framework and a careful assess-ment of prior literature investigating the relationshipbetween MA use and HIV risk behaviour. We hypothe-sized that MA use among sexual minority drug userswould be associated with differing exposure to indivi-dual, social, and structural HIV vulnerabilities. In aneffort to build on previous studies [16,23,24], we soughtnot only to examine individual-level HIV risk behaviourbut also contextual factors including homelessness,neighbourhood of residence, the consumption of drugsin public, and the regulation of these spaces by lawenforcement personnel. We also considered the relation-ship between MA use and physical violence and depres-sion, which have been identified as independent riskfactors for HIV infection [9,25]. Finally, we hypothesizedthat the relationship between MA use and these factorswould differ significantly between sexual minority malesand females.Variables of InterestThe primary outcome of interest was ascertained byexamining responses to the questions, “In the last sixmonths, did you use non-injection crystal methampheta-mine?” and “In the last six months, did you inject crystalmethamphetamine?” Participants who responded “yes”to either or both questions were defined as crystalmethamphetamine (MA) users in all subsequent ana-lyses. We also determined the proportion of partici-pants reporting daily or greater use of injection ornon-injection MA use in the past 6 months, respec-tively. All variables examined in this study, includingthe outcomes and independent variables of interest,were assessed consistently and equivalently across allthree studies.Based on prior literature examining MA use amongmarginalised populations [12,26-29], we assessed asexplanatory variables a broad set of sociodemographiccharacteristics, drug use variables, sexual activities, mar-kers of violence and depression, and contextual factors.These variables were also chosen to represent both“micro”- (i.e., the immediate social environment of druguse) and “macro"- (i.e., the societal, economic, and legalcontext that structure drug use and harm) levels articu-lated by the risk environment framework [19]. Sociode-mographic characteristics examined included age (peryear older), Aboriginal ancestry (yes versus no), currentrelationship status (single/dating versus married/regularpartner), and baseline HIV status (positive versus nega-tive). All other variables (unless otherwise indicated)referred to behaviours or activities in the past 6 monthssince the date of the interview. Drug use variablesassessed included other stimulant use (i.e., non-injectioncocaine use and crack use, respectively), any injectiondrug use, experiencing a non-fatal overdose, and bingedrug use. As defined previously [30], the latter was oper-ationalised as the self-reported use of drugs more oftenthan usual. We also examined the following sexualactivities: number of casual or regular partners exclud-ing those in the context of sex work (>1 versus ≤1); anyvaginal or anal unprotected intercourse with casual orregular partners (yes versus no); and sex trade work,defined as a categorical variable with “no” as the refer-ence level and consistent condom use with all clientsand any unprotected intercourse with clients as the sec-ond and third levels, respectively. We ascertained invol-vement in (i.e., committing) and exposure to (i.e.,experiencing) physical violence (yes versus no). We alsoused the Center for Epidemiologic Studies DepressionScale (CES-D) with a cut-off of ≥16 to measure the levelof depressive symptomatology among participants [31].Finally, contextual factors examined included: residencyin the Downtown South (DTS), an area known as amixed business and entertainment district that is alsoinhabited by a large street youth population [32]; home-lessness (yes versus no); having a warrant or arearestriction (i.e., “no go zone”) impact access to servicesor influence where drugs are consumed or purchased(yes versus no); and using drugs in public spaces (>75%of the time versus ≤75% of the time). Warrants and arearestrictions are legal orders to restrict access to certainareas of the city, and are commonly issued by law enfor-cement personnel in an attempt to disrupt crime andreduce street level disorder [33].Marshall et al. BMC Public Health 2011, 11:20http://www.biomedcentral.com/1471-2458/11/20Page 3 of 10Statistical AnalysisAs a preliminary analysis, we compared the baselinesociodemographic characteristics and MA use patternsbetween heterosexual and sexual minority participants,stratified by biological sex at birth. The Pearson chi-square test was used to compare categorical variablesand the Wilcoxon rank sum test was used for continu-ous variables. We then identified the longitudinal corre-lates of MA use by using generalized estimatingequations (GEE) with a logit link for binary outcomes.GEE were appropriate for this analysis since the factorsassociated with recent MA use over the baseline andfour follow-up periods were serial (i.e., time-dependent)variables. GEE account for the correlation betweenrepeated measures for each subject; thus, valid estimatesof association and standard errors are obtained [34].Since GEE models incorporate periods during whichparticipants report engaging and not engaging in theoutcome, data from all baseline and follow-up interviewswere used in this analysis.Since a primary objective of this study was to deter-mine whether the correlates of MA use differed betweenmales and females, we stratified the analyses by biologi-cal sex at birth and constructed two multivariate mod-els. We applied a modified backward stepwise procedureto select covariates based on two criteria: the Akaikeinformation criterion (AIC) and type-III p-values [35].Lower AIC values indicate a better overall fit and lowerp-values indicate higher variable significance. Startingwith a full model containing all variables that were sig-nificant in bivariate analyses at p < 0.10, covariates wereremoved sequentially in order of decreasing p-values. Tocompensate for potential variations in recruitment andselection procedures between studies, we also adjustedeach model for cohort of enrolment. At each step, thep-values of each variable and the overall AIC wererecorded, with the final model having the lowest AIC.Statistical analysis was conducted using SAS version9.1.3 (SAS Institute Inc., Cary, North Carolina, USA)and all p-values are two-sided.ResultsSample CharacteristicsBetween September 2005 and May 2008, 2109 uniqueindividuals were enrolled into the ARYS, VIDUS orACCESS cohorts. A total of 14 (0.7%) refused to reporttheir sex at birth or current sexual/gender identity andwere thus excluded for the analysis. Of the 2095 eligibleparticipants, 1389 (66.3%) were male and 706 (33.7%)were female. Among all participants, the median age atbaseline was 37.0 (IQR: 24.7 - 45.4) and 641 (30.6%)were of Aboriginal ancestry. The majority identifiedtheir sexual or gender identity as heterosexual (n =1847, 88.2%), followed by bisexual (n = 168, 8.0%), gay(n = 43, 2.1%), lesbian (n = 9, 0.4%), and transsexual,transgendered, or other (n = 28, 1.3%). Among thosewho reported their biological sex at birth as female, 144(20.4%) identified as a sexual minority compared to only7.5% (n = 104) of biological males.Baseline Methamphetamine UseSociodemographic characteristics and methamphetamineuse patterns for males and females stratified by sexualorientation are displayed in Table 1. At baseline, sexualminority males were more likely to be younger (median= 33 versus 39, p = 0.001), HIV positive (40.4% versus21.2%, p < 0.001), and of Aboriginal ancestry (40.4% ver-sus 23.7%, p < 0.001). In contrast, sexual minorityfemales were less likely to be of Aboriginal ancestry(33.3% versus 43.9%, p = 0.023). Among both males andfemales, sexual minority participants were significantlymore likely to report injection and non-injection MAuse in the past 6 months (Table 1). Notably, over half(62.1%) of sexual minority males reported recently usingMA, and a significant proportion (16.7%) reportedinjecting MA at least daily. Approximately half (n = 142,57.3%) of sexual minority participants reported havingused MA for at least a year since the date of the base-line interview.Longitudinal Correlates of Methamphetamine UseIn Table 2, we report the results of the longitudinal ana-lysis examining the factors associated with MA useamong sexual minority males. Bivariate analyses indi-cated that male MA users were more likely to experi-ence a variety of sexual HIV risks and vulnerabilities,including for example multiple recent sex partners(odds ratio [OR] = 1.91, p = 0.002), unprotected inter-course (OR = 1.86, p = 0.004), and unprotected inter-course in the context of sex work (OR = 3.25, p =0.005). MA using men were also more likely to reportinjection drug use (OR = 2.31, p = 0.004), experiencephysical violence (OR = 1.76, p = 0.004), commit physi-cal violence (OR = 1.90, p = 0.025) and exhibit depres-sive symptoms (OR = 1.79, p = 0.010). In multivariateanalysis, independent correlates of MA use among sex-ual minority males included: younger age (adjusted oddsratio [AOR] = 0.93, p = 0.011), Aboriginal ancestry(AOR = 2.59, p = 0.019), injection drug use (adjustedodds ratio [AOR] = 3.98, p < 0.001), unprotected sexualintercourse (AOR = 1.62, p = 0.048), increased depres-sive symptoms (AOR = 1.67, p = 0.044), and having anarea restriction impact access to services or influencewhere drugs are used or purchased (AOR = 4.18, p =0.008).Increased sexual HIV vulnerabilities were alsoobserved among MA-using sexual minority females(Table 3). For example, females reporting recent MAMarshall et al. BMC Public Health 2011, 11:20http://www.biomedcentral.com/1471-2458/11/20Page 4 of 10use were more likely to have multiple regular or casualsex partners (OR = 1.55, p = 0.029). Several associationsthat were observed among MA-using males were alsosignificant among females. For example, female MAusers were younger (OR = 0.95, p = 0.005), more likelyto inject drugs (OR = 1.68, p = 0.011), and reported ele-vated rates of unprotected intercourse in the context ofsex work (OR = 3.27, p = 0.001). In contrast, MA-usingfemales were less likely to be of Aboriginal ancestry (OR= 0.41, p = 0.012).In a multivariate analysis, several unique correlates ofMA use emerged among sexual minority females. Incontrast to males, MA-using females were more likelyto reside in the Downtown South neighbourhood (AOR= 1.60, p = 0.047). Furthermore, MA use among sexualminority females was independently associated withunprotected intercourse with sex trade clients (AOR =2.62, p = 0.027). Similar to males, MA-using femaleswere more likely to report injection drug use (AOR =2.49, p = 0.002).Table 1 Baseline sociodemographic characteristics and methamphetamine use patterns among ARYS, VIDUS, andACCESS participants, stratified by biological sex at birth and self-identified sexual orientation (n, % unless otherwiseindicated)Male (N = 1389) Female (N = 706)Characteristic Sexual Minority*(n = 104)Heterosexual(n = 1285)OR(95%CI)p-valueSexual Minority*(n = 144)Heterosexual(n = 562)OR (95%CI)p-valueAge (median, IQR) 33 (24 - 42) 39 (25 - 47) 0.97 (0.95 -0.99)0.001 31 (23 - 41) 35 (24 - 44) 0.98 (0.97 -1.00)0.053Aboriginal ancestryYes 42 (40.4) 305 (23.7) 2.18 (1.44 -3.29)<0.001 48 (33.3) 246 (43.9) 0.64 (0.44 -0.94)0.023No 62 (59.6) 980 (76.3) 96 (66.7) 315 (56.2)Relationship statusSingle/dating 73 (70.2) 927 (72.4) 0.90 (0.58 -1.39)0.634 90 (62.5) 307 (55.4) 1.34 (0.92 -1.95)0.127Married/regularpartner31 (29.8) 354 (27.6) 54 (37.5) 247 (44.6)HIV statusPositive 42 (40.4) 272 (21.2) 2.52 (1.67 -3.82)<0.001 41 (28.5) 159 (28.3) 1.01 (0.67 -1.51)0.966Negative 62 (59.6) 1013 (78.8) 103 (71.5) 403 (71.7)Any meth use†Yes 64 (62.1) 388 (30.5) 3.74 (2.47 -5.67)<0.001 58 (40.3) 150 (27.2) 1.80 (1.23 -2.64)0.003No 39 (37.9) 884 (69.5) 86 (59.7) 401 (72.8)Any non-injectionmeth use†Yes 38 (36.5) 223 (17.5) 2.71 (1.78 -4.15)<0.001 36 (25.0) 89 (16.0) 1.75 (1.12 -2.71)0.013No 66 (63.5) 1050 (82.5) 108 (75.0) 466 (84.0)Daily non-injectionmeth use†Yes 11 (10.6) 39 (3.1) 3.72 (1.84 -7.50)<0.001 8 (5.6) 20 (3.7) 1.56 (0.67 -3.62)0.296No 93 (89.4) 1226 (96.9) 135 (94.4) 527 (96.3)Any injection methuse†Yes 43 (41.4) 262 (20.4) 2.75 (1.82 -4.15)<0.001 39 (27.1) 100 (18.0) 1.69 (1.10 -2.59)0.016No 61 (58.6) 1021 (79.6) 105 (72.9) 455 (82.0)Daily injection methuse†Yes 17 (16.7) 45 (3.5) 5.45 (3.00 -9.95)<0.001 9 (6.4) 16 (2.9) 2.27 (0.98 -5.24)0.066No 85 (83.3) 1229 (96.5) 132 (93.6) 532 (97.1)Notes: * “sexual minority” refers to lesbian, gay, bisexual, transgendered, transsexual, or other orientation; † refers to activities in the past 6 months.Marshall et al. BMC Public Health 2011, 11:20http://www.biomedcentral.com/1471-2458/11/20Page 5 of 10DiscussionIn the current study, we observed a high prevalence ofMA use among sexual minority males and females incomparison to heterosexual participants. We also foundthat, consistent with the risk environment framework,MA use was associated with an array of individual,social, and contextual HIV-related risks and vulnerabil-ities among sexual minority drug users.Although some correlates of MA use (e.g., youngerage and injection drug use) were significant for bothsexes, several important differences were observed. Forexample, unprotected intercourse involving regular orcasual partners was more common among males whoreported using methamphetamine, while unprotectedintercourse in the context of sex work was associatedwith MA use among females. Furthermore, only MA-using males were more likely to experience depressivesymptoms and report having area restrictions (i.e., “nogo” zones) impact access to services of influence wheredrugs are used or purchased. These findings may be dueto the fact that sexual minority males reported heavierMA use patterns compared to females, and thus may bemore likely to experience individual (i.e., depressivesymptoms) and contextual (i.e., exposure to law enforce-ment) MA-related sequelae. Finally, Aboriginal ancestrywas positively associated with MA use among males butinversely associated with MA use among females.Consistent with other studies [7,8,36], MA use waslinked with unprotected intercourse among sexual min-ority men. Although we were unable to ascertain thecontext in which instances of unprotected intercourseoccurred, we point to other research indicating thathomeless sexual minority males frequently experiencesexual victimization and abuse from partners [37].Although more research is required to fully elucidatecasual mechanisms, we hypothesize that the relationshipbetween sexual risk and MA use observed among thissample of street-involved sexual minority men is less afunction of desire to enhance sex but is in fact a markerof increased vulnerability within sexual relationships.Table 2 Longitudinal analysis of factors associated with crystal methamphetamine use† among sexual minority* males(n = 104)Bivariate MultivariateCharacteristic Odds Ratio 95% CI p-value Adjusted Odds Ratio 95% CI p-valueSociodemographic CharacteristicsAge (per year) 0.92 0.89 - 0.96 <0.001 0.93 0.88 - 0.98 0.011Aboriginal ancestry (yes vs. no) 2.37 1.17 - 4.79 0.016 2.59 1.17 - 5.77 0.019Relationship status (single/dating vs. married/partner) 0.96 0.65 - 1.42 0.842HIV Status (positive vs. negative) 0.50 0.24 - 1.00 0.051Drug UseNon-injection cocaine use† (yes vs. no) 2.44 1.09 - 5.44 0.029Crack use† (yes vs. no) 1.47 0.89 - 2.43 0.133Any injection drug use† (yes vs. no) 2.31 1.30 - 4.11 0.004 3.98 1.85 - 8.57 <0.001Overdose† (yes vs. no) 1.52 0.83 - 2.77 0.172Binge drug use† (yes vs. no) 1.50 0.90 - 2.50 0.118Sexual ActivitiesNumber of sex partners† (>1 vs. ≤1) 1.91 1.28 - 2.86 0.002Unprotected intercourse† (yes vs. no) 1.86 1.22 - 2.84 0.004 1.62 1.01 - 2.60 0.048Sex trade work† (ref = no sex trade work)Consistent condom use with clients† (yes vs. ref) 2.79 1.62 - 4.82 <0.001Any unprotected sex with clients† (yes vs. ref) 3.25 1.44 - 7.37 0.005Violence & DepressionExperience physical violence† (yes vs. no) 1.76 1.20 - 2.59 0.004 1.47 0.93 - 2.32 0.100Commit physical violence† (yes vs. no) 1.90 1.09 - 3.31 0.025Clinical depression (CES-D‡ ≥16 vs. <16) 1.79 1.15 - 2.79 0.010 1.67 1.01 - 2.76 0.044Contextual FactorsDowntown South residency (yes vs. no) 1.45 0.90 - 2.34 0.124Homeless† (yes vs. no) 1.76 1.00 - 3.09 0.050Area restrictions influence drug use (yes vs. no) 4.02 0.87 - 18.54 0.075 4.18 1.46 - 11.95 0.008Use drugs in public† (>75% vs. ≤75% of the time) 1.53 0.96 - 2.43 0.073Notes: model adjusted for cohort of recruitment; * “sexual minority” refers to lesbian, gay, bisexual, transgendered, transsexual, or other orientation; † refers toactivities in the past 6 months; ‡ CES-D refers to the Center for Epidemiologic Studies Depression Scale.Marshall et al. BMC Public Health 2011, 11:20http://www.biomedcentral.com/1471-2458/11/20Page 6 of 10A similar pathway may also explain the marginal asso-ciation between MA use and experiencing physical vio-lence observed among males in this study.In multivariate analysis, among the subsample offemales engaging in sex work, MA use was associatedwith unprotected intercourse with clients. This findingcan be situated within a growing literature demonstrat-ing how social and structural inequities hinder the indi-vidual agency of drug-using survival sex workers topractice HIV prevention and harm reduction with cli-ents [38]. In a recent study of female sex workers (FSW)in Vancouver, Canada, Shannon et al. [39] demonstratedthat MA use is associated with living and working inmarginalised public spaces (e.g., industrial areas). Theseareas have been shown in previous research to be set-tings of increased risk of violence and pressure from cli-ents to engage in unprotected sex [40]. Our resultssupport this work and indicate that MA use may aug-ment the adverse impact of social-structural factors inthe production of HIV risk among sexual minoritywomen involved in survival sex work.The strongest correlate of MA use among sexual min-ority men was reporting that a warrant or area restric-tion impacted access to services or influenced wheredrugs are consumed or purchased. The socio-legal regu-lation of public space and its negative impact on thehealth of homeless people and street-level drug usershas been described previously [41]. Recent work alsosuggests that the displacement of street-involved youngpeople using warrants or area restrictions exacerbatesstigma and increases sexual vulnerability and HIV risk[42]. Our findings suggest that having one’s movementsrestricted may also encourage transitions in drug use(including initiation of MA use), due perhaps to theforced removal of drug users from normative environ-ments and social networks. It is also possible that MAusers are at an increased risk of incarceration and otherinteractions with the legal system, and are thus moreTable 3 Longitudinal analysis of factors associated with crystal methamphetamine use† among sexual minority*females (n = 144)Bivariate MultivariateCharacteristic Odds Ratio 95% CI p-value Adjusted Odds Ratio 95% CI p-valueSociodemographic CharacteristicsAge (per year) 0.95 0.92 - 0.99 0.005Aboriginal ancestry (yes vs. no) 0.41 0.21 - 0.82 0.012 0.55 0.25 - 1.21 0.137Relationship (single/dating vs. married/partner) 1.07 0.76 - 1.49 0.708HIV Status (positive vs. negative) 0.62 0.90 - 1.30 0.209Drug UseNon-injection cocaine use† (yes vs. no) 1.79 1.06 - 3.04 0.030 1.66 0.94 - 2.92 0.079Crack use† (yes vs. no) 0.95 0.71 - 1.27 0.730Any injection drug use† (yes vs. no) 1.68 1.13 - 2.50 0.011 2.49 1.42 - 4.39 0.002Overdose† (yes vs. no) 1.47 0.90 - 2.41 0.126Binge drug use† (yes vs. no) 1.18 0.77 - 1.81 0.452Sexual ActivitiesNumber of sex partners† (>1 vs. ≤1) 1.55 1.05 - 2.30 0.029Unprotected intercourse† (yes vs. no) 0.97 0.65 - 1.45 0.897Sex trade work† (ref = no sex trade work)Consistent condom use with clients† (yes vs. ref) 1.30 0.88 - 1.93 0.189 1.16 0.72 - 1.87 0.543Any unprotected sex with clients† (yes vs. ref) 3.27 1.60 - 6.68 0.001 2.62 1.12 - 6.14 0.027Violence & DepressionExperience physical violence† (yes vs. no) 1.24 0.88 - 1.75 0.210Commit physical violence† (yes vs. no) 1.12 0.81 - 1.54 0.499Clinical depression (CES-D‡ ≥16 vs. <16) 0.85 0.66 - 1.09 0.204Contextual FactorsDowntown South residency (yes vs. no) 1.45 1.00 - 2.10 0.053 1.60 1.01 - 2.54 0.047Homeless† (yes vs. no) 1.19 0.86 - 1.64 0.299Area restrictions influence drug use (yes vs. no) 0.59 0.28 - 1.23 0.160Use drugs in public† (>75% vs. ≤75% of the time) 1.18 0.77 - 1.81 0.446Notes: model adjusted for cohort of recruitment; * “sexual minority” refers to lesbian, gay, bisexual, transgendered, transsexual, or other orientation; † refers toactivities in the past 6 months; ‡ CES-D refers to the Center for Epidemiologic Studies Depression Scale.Marshall et al. BMC Public Health 2011, 11:20http://www.biomedcentral.com/1471-2458/11/20Page 7 of 10likely to be affected by punitive policies such as warrantsand area restrictions. This form of marginalisation (pro-duced by policies and practices meant to reduce expo-sure to street-level drug use and violence) is oneexample of a population-level intervention that mayexacerbate inequity and worsen the health of vulnerablegroups [43].These findings also support the urgent need forincreased resources and programming directed towardsLGBT people who use methamphetamine. In order toinform more effective interventions to reduce the harmsassociated with MA, researchers must clearly articulatehow social/structural processes impact the health of sex-ual minorities. Once clearly identified, these factors canthen be the target of broad sets of evidence-based inter-ventions to reduce health inequities and improve overallhealth. For example, changes in government policyalong with community mobilization and solidarity pro-grams have been shown to be highly successful at redu-cing HIV risk among survival sex workers [44].Programs that support capacity-building in marginalisedcommunities have also been shown to reduce healthinequity and improve health outcomes [45]. Althoughfurther research is required to elucidate the potentialimpact of specific enforcement practices (e.g., arearestrictions) on MA use and related harms, improvedcoordination between policing and public health initia-tives may represent another opportunity to prevent the(un)-intended consequences of public policies meant toreduce crime and street disorder [46]. Finally, additionalresearch is required to identify specific programmaticneeds of subpopulations within sexual minority commu-nities, including for example transgendered youth.To complement structural interventions, some beha-vioural approaches (e.g., cognitive behavioural therapy)offer promise [47]. For example, LGBT-specific sub-stance abuse treatment programs have been found toreduce engagement in high-risk sex among drug-usinggay men [48]. Harm reduction programs, particularlythose offering tailored services for MA users, are effec-tive and well received by clients [49]. Finally, given theassociations between Aboriginal ancestry, sexual orienta-tion, and MA use observed in this study, methampheta-mine-specific programming should carefully identify themanner in which cultural and sexual identities shapedrug use and HIV risk within specific contexts andsettings.This study has a number of limitations that should benoted. The ARYS, VIDUS, and ACCESS cohorts are notrandom samples of the eligible population; thus, findingsmay not necessarily be generalizable to other urbanareas in which MA use is prevalent. The small samplesizes may have resulted in insufficient power to detecttrue associations, particularly after adjustment for con-founding. Furthermore, data from three studies with dif-ferent inclusion criteria were combined and analysed,which may have resulted in cohort or selection effects.To mitigate the potential impact of these biases, all sam-pling and data collection procedures were harmonized,and all multivariate models were adjusted for cohort ofrecruitment. We note that all behaviours ascertained inthis study were self-reported, and we were unable toconfirm MA use with urine samples or other measures.We also recognize that our primary analysis wasrestricted to individuals who self-identified as a sexualminority; therefore, heterosexual-identified individualswho engaged in same-sex activity were excluded. Wechose not to rely on behavioural eligibility criteria (e.g.,MSM), as we feel, as do others [50], that ignoring sexualidentity in HIV prevention efforts obscures the socialdimensions of sexuality that are critical for the develop-ment of effective and culturally relevant public healthinterventions. However, we note that public healthefforts should be made to provide appropriate servicesfor non-LGBT identifying MSM/WSW, including pro-grams that explicitly acknowledge and accept diversesexual experiences and identities [51]. We were unableto ascertain motivations for MA use, which if examinedmay have accounted some of the observed differences inthe characteristics and consequences of MA usebetween male and female participants in this study.Finally, although our data are longitudinal, we do notwish to imply that this analysis provides thoroughinsight into the causal pathways linking MA use andHIV risk with broader social and structural inequities.ConclusionWe have demonstrated in a longitudinal data set a highprevalence of MA use among a cohort of street-involvedsexual minority drug users. To our knowledge, this isthe first study to extend the risk environment approachas a theoretical foundation from which to understandthe contexts of risk associated with MA use amongLGBT populations. Consistent with the risk environ-ment framework, MA use was associated with distinctsets of individual, social, and structural HIV risks andvulnerabilities among women and men, respectively;therefore, comprehensive interventions that involve sec-tors outside of health (e.g., housing, law enforcement),in addition to drug-specific approaches tailored toLGBT populations, are required to reduce HIV vulner-ability and MA-related harms. Finally, researchers andpublic health practitioners must identify multi-sectorpopulation-level interventions that do not exacerbateinequity but successfully mitigate health inequitiesamong vulnerable populations.Marshall et al. BMC Public Health 2011, 11:20http://www.biomedcentral.com/1471-2458/11/20Page 8 of 10AcknowledgementsThe authors thank the study participants for their contribution to theresearch, as well as current and past investigators and staff. We wouldspecifically like to thank Deborah Graham, Peter Vann, Caitlin Johnston,Steve Kain, and Calvin Lai for their research and administrative assistance.The ARYS study was supported by the US National Institutes of Health (NIH)grant R01-DA028532 as well as the Canadian Institutes of Health Research(CIHR) grant MOP-102742. The VIDUS study was supported by NIH (R01-DA011591). The ACCESS study was supported by NIH (R01-DA021525) andCIHR (MOP-79297). All studies are supported by a CIHR team grant RAA-79918. TK is supported by the Michael Smith Foundation for Health Research(MSFHR) and the CIHR. BDLM is supported by senior graduate traineeawards from MSFHR and CIHR.Author details1British Columbia Centre for Excellence in HIV/AIDS, St. Paul’s Hospital, 608-1081 Burrard Street, Vancouver, BC, V6Z 1Y6, Canada. 2School of Populationand Public Health, University of British Columbia, 2206 East Mall, Vancouver,BC, V6T 1Z3, Canada. 3Department of Medicine, University of BritishColumbia, St. Paul’s Hospital, 608-1081 Burrard Street, Vancouver, BC, V6Z1Y6, Canada. 4Department of Psychiatry, University of California, 9500 GilmanDrive, La Jolla, California, 92093-0680, USA.Authors’ contributionsTK had full access to all of the data and takes responsibility for the integrityof the results and the accuracy of the statistical analysis. BM, TK, and JSconceived the study concept and design, and BM was responsible for thestatistical analysis and composition of the manuscript. BM led theinterpretation of the results, with significant scientific input from JS, EW, TP,JM, and TK. The manuscript was edited and revised by BM, EW, JS, TP, JM,and TK. All authors read and approved the final version of the manuscript.Competing interestsDr Montaner reported receiving educational grants from and serving as anad hoc advisor to or speaking at various events sponsored by AbbottLaboratories, Agouron Pharmaceuticals Inc, Boehringer IngelheimPharmaceuticals Inc, Borean Pharma AS, Bristol-Myers Squibb, DuPontPharma, Gilead Sciences, GlaxoSmithKline, Hoffmann-La Roche, ImmuneResponse Corporation, Incyte, Janssen-Ortho Inc, Kucera PharmaceuticalCompany, Merck Frosst Laboratories, Pfizer Canada Inc, Sanofi Pasteur, ShireBiochem Inc, Tibotec Pharmaceuticals Ltd, and Trimeris Inc. All other authorsdeclare that they have no competing interests.Received: 28 July 2010 Accepted: 7 January 2011Published: 7 January 2011References1. Mayer KH, Bradford JB, Makadon HJ, Stall R, Goldhammer H, Landers S:Sexual and gender minority health: what we know and what needs tobe done. 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Arch Sex Behav 2008, 37:748-762.Pre-publication historyThe pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/11/20/prepubdoi:10.1186/1471-2458-11-20Cite this article as: Marshall et al.: Pathways to HIV risk and vulnerabilityamong lesbian, gay, bisexual, and transgendered methamphetamineusers: a multi-cohort gender-based analysis. BMC Public Health 201111:20.Submit your next manuscript to BioMed Centraland take full advantage of: • Convenient online submission• Thorough peer review• No space constraints or color figure charges• Immediate publication on acceptance• Inclusion in PubMed, CAS, Scopus and Google Scholar• Research which is freely available for redistributionSubmit your manuscript at www.biomedcentral.com/submitMarshall et al. BMC Public Health 2011, 11:20http://www.biomedcentral.com/1471-2458/11/20Page 10 of 10


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